scholarly journals Why not model spoken word recognition instead of phoneme monitoring?

2000 ◽  
Vol 23 (3) ◽  
pp. 349-350
Author(s):  
Jean Vroomen ◽  
Beatrice de Gelder
Keyword(s):  
Speech Recognition ◽  
Word Recognition ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Detailed Account ◽  
Phoneme Recognition ◽  
Decision Stage ◽  
Recognition Process ◽  
Monitoring Task ◽  
Phoneme Monitoring

Norris, McQueen & Cutler present a detailed account of the decision stage of the phoneme monitoring task. However, we question whether this contributes to our understanding of the speech recognition process itself, and we fail to see why phonotactic knowledge is playing a role in phoneme recognition.

A spoken word recognition system based on phoneme recognition

1983 ◽  
Vol 2 (2-3) ◽  
pp. 237-239 ◽  
Author(s):  
Takao Irumano ◽  
Hisanori Kanasashi ◽  
Kunio Akiba ◽  
Yasuo Mafune
Keyword(s):  
Word Recognition ◽  
Spoken Word Recognition ◽  
Recognition System ◽  
Spoken Word ◽  
Phoneme Recognition

scholarly journals Computational modelling of spoken-word recognition processes

2010 ◽  
Vol 18 (1) ◽  
pp. 136-164 ◽  
Author(s):  
Odette Scharenborg ◽  
Lou Boves
Keyword(s):  
Word Recognition ◽  
Word Processing ◽  
Goodness Of Fit ◽  
Computational Models ◽  
Spoken Word Recognition ◽  
Computational Modelling ◽  
Spoken Word ◽  
Recognition Process ◽  
Depth Analysis ◽  
Cognitive Plausibility

Computational modelling has proven to be a valuable approach in developing theories of spoken-word processing. In this paper, we focus on a particular class of theories in which it is assumed that the spoken-word recognition process consists of two consecutive stages, with an ‘abstract’ discrete symbolic representation at the interface between the stages. In evaluating computational models, it is important to bring in independent arguments for the cognitive plausibility of the algorithms that are selected to compute the processes in a theory. This paper discusses the relation between behavioural studies, theories, and computational models of spoken-word recognition. We explain how computational models can be assessed in terms of the goodness of fit with the behavioural data and the cognitive plausibility of the algorithms. An in-depth analysis of several models provides insights into how computational modelling has led to improved theories and to a better understanding of the human spoken-word recognition process.

No compelling evidence against feedback in spoken word recognition

2000 ◽  
Vol 23 (3) ◽  
pp. 348-349
Author(s):  
Michael K. Tanenhaus ◽  
James S. Magnuson ◽  
Bob McMurray ◽  
Richard N. Aslin
Keyword(s):  
Speech Recognition ◽  
Word Recognition ◽  
Strong Evidence ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Behavioral Data ◽  
Recognition Problem ◽  
Compelling Evidence ◽  
Empirical Results ◽  
Occam’S Razor

Norris et al.'s claim that feedback is unnecessary is compromised by (1) a questionable application of Occam's razor, given strong evidence for feedback in perception; (2) an idealization of the speech recognition problem that simplifies those aspects of the input that create conditions where feedback is useful; (3) Norris et al.'s use of decision nodes that incorporate feedback to model some important empirical results; and (4) problematic linking hypotheses between crucial simulations and behavioral data.

Tracking the time course of lexical access in spoken word recognition

1997 ◽  
Author(s):  
Paul D. Allopenna ◽  
James S. Magnuson ◽  
Michael K. Tanenhaus
Keyword(s):  
Word Recognition ◽  
Lexical Access ◽  
Time Course ◽  
Spoken Word Recognition ◽  
Spoken Word
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